A new methodology for bare soils detection using extended Bragg covariance matrix forms.

This paper presents a new methodology for detecting bare rough soil in non-urban areas using synthetic aperture radar data. Our approach involves matching the covariance/coherence matrix to the extended Bragg (xBragg) model. Our method uses automatic OTSU's thresholding based on roughness angles histogram to determine output classes and avoid complex calculations, making it suitable for onboard computing. The procedure is suitable for a range of soil roughness but not for highly specular surfaces. The performance of the suggested methodology was evaluated using simulated data and real L- and P-band SAR datasets from two different sites with various features. Our results demonstrate the effectiveness of the method for rough agricultural and natural surfaces, with good performance and a success rate of up to about 95 % across a wide range of roughness values from 0 ∘ to 65 ∘ . [ABSTRACT FROM AUTHOR]